Manager, Senior Manager of Data Science

Summary

Join Typeform's Data & Insights team as a Manager or Senior Manager of Data Science and lead a team of 4 in building AI-first experiences. You will define the team's roadmap, mature AI capabilities, and partner with Product, Engineering, and Analytics. Responsibilities span experimentation design to ML model deployment, fostering a collaborative environment. The ideal candidate has 6+ years of experience in data science or a related field, with leadership experience and a strong foundation in statistics and experimentation. Proficiency in Python and SQL is required, along with excellent communication skills. The role involves strategic leadership, technical execution, and org-wide impact.

Requirements

• 6+ years of experience in data science, machine learning, or a related field, with at least 1–2 years in a leadership or technical mentorship role
• Proven track record of delivering ML-powered product features or decision-support systems in a production environment
• Strong foundation in statistics, experimentation, and causal inference—plus deep experience with model development and lifecycle management
• Proficiency in Python (and libraries such as pandas, scikit-learn, PyTorch, or TensorFlow) and SQL; familiarity with ML orchestration tools and cloud platforms
• Excellent communication skills—able to translate technical work into business outcomes and influence stakeholders at all levels

Responsibilities

• Lead, mentor, and develop a team of Data Scientists and ML Engineers—fostering a growth mindset, shared ownership, and deep technical curiosity
• Define and drive the roadmap for applied ML and AI initiatives across core product areas, balancing quick wins with foundational investments
• Partner cross-functionally with Product, Engineering, and Analytics to identify and prioritize high-impact opportunities for ML and experimentation
• Collaborate with Data Engineering and Analytics Engineering to ensure scalable data pipelines, model monitoring, and deployment infrastructure
• Champion a culture of reproducibility, documentation, and scientific rigor
• Contribute to modeling strategy, experimentation frameworks, and architecture decisions—reviewing code, shaping methodology, and guiding best practices
• Support the development and deployment of machine learning models that power intelligent product features and internal automations
• Guide experimentation design and causal inference approaches to validate product impact and customer behavior hypotheses
• Partner with stakeholders to translate ambiguous business problems into data science opportunities with clear success criteria
• Help define our long-term AI/ML strategy and tooling roadmap—including model observability, feature stores, and governance practices
• Represent the Data Science & ML Engineering function in strategic planning discussions, technical design reviews, and cross-functional working groups
• Advocate for ethical and responsible AI practices, ensuring fairness, transparency, and explainability in our ML systems
• Support hiring, onboarding, and career development for technical talent within the team

Preferred Qualifications

• Experience managing hybrid teams that include both Data Scientists and ML Engineers
• Exposure to modern MLOps tooling (e.g. MLflow, Feature Store, SageMaker, Vertex AI)
• Familiarity with unstructured data modeling (e.g. NLP, embeddings, LLMs) and GenAI product patterns
• Experience working in product-led or B2B SaaS environments
• You bring a coaching mindset and love growing talent as much as shipping great models